CVE-2025-10279

In mlflow version 2.20.3, the temporary directory used for creating Python virtual environments is assigned insecure world-writable permissions (0o777). This vulnerability allows an attacker with write access to the `/tmp` directory to exploit a race condition and overwrite `.py` files in the virtual environment, leading to arbitrary code execution. The issue is resolved in version 3.4.0.

On a shared GPU cluster where 20 data scientists run MLflow experiments, an adversary with a low-privilege shell account monitors inotify events on /tmp watching for MLflow venv directory creation. When MLflow creates /tmp/mlflow-venv-XXXX/ with 0o777 permissions, the attacker has a brief window to overwrite a commonly imported .py file (e.g., site.py, importlib bootstrap) with a malicious payload before MLflow's Python interpreter executes it. The injected code runs in the MLflow process context, harvesting AWS/GCP credentials from environment variables, exfiltrating model artifacts from the registry, and optionally modifying model weights before they're logged — a silent supply chain attack on the ML pipeline that produces poisoned models deployed to production.